State estimation of system with bounded uncertain parameters: interval multi-model approach

Abstract : The objective of this study is the analysis of dynamic systems represented by multi-model with variable parameters. Changes in these parameters are unknown but bounded. Since it is not possible to estimate these parameters over time, the simulation of such systems requires to consider all possible values taken by these parameters. More precisely, the goal is to determine, at any moment, the smallest set containing all the possible values of the state vector simultaneously compatible with the state equations and with a priori known bounds of the uncertain parameters. This set will be characterized by two trajectories corresponding to the lower and upper limits of the state at every moment. This characterization can be realized by a direct simulation of the system, given the bounds of its parameters. It can also be implemented with a Luenberger type observer, fed with the system measurements.
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Dalil Ichalal, Benoît Marx, Didier Maquin, José Ragot. State estimation of system with bounded uncertain parameters: interval multi-model approach. International Journal of Adaptive Control and Signal Processing, Wiley, 2018, 32 (3), pp.480-493. ⟨10.1002/acs.2855⟩. ⟨hal-01657658⟩

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